Overview

Brought to you by YData

Dataset statistics

Number of variables9
Number of observations1063
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory83.0 KiB
Average record size in memory80.0 B

Variable types

Numeric8
Text1

Alerts

Average_SAT_Score is highly overall correlated with Completion_Rate and 4 other fieldsHigh correlation
Completion_Rate is highly overall correlated with Average_SAT_Score and 4 other fieldsHigh correlation
In-State_Tuition is highly overall correlated with Average_SAT_Score and 3 other fieldsHigh correlation
Median_Earnings_10_Years_After is highly overall correlated with Average_SAT_Score and 4 other fieldsHigh correlation
Out-of-State_Tuition is highly overall correlated with Average_SAT_Score and 4 other fieldsHigh correlation
Pell_Grant_Rate is highly overall correlated with Average_SAT_Score and 3 other fieldsHigh correlation

Reproduction

Analysis started2024-09-24 19:54:25.341549
Analysis finished2024-09-24 19:54:31.884663
Duration6.54 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

Admission_Rate
Real number (ℝ)

Distinct973
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.71292098
Minimum0.0324
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:31.955151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.0324
5-th percentile0.17787
Q10.6123
median0.7662
Q30.876
95-th percentile0.9695
Maximum1
Range0.9676
Interquartile range (IQR)0.2637

Descriptive statistics

Standard deviation0.22342307
Coefficient of variation (CV)0.31339107
Kurtosis0.99987747
Mean0.71292098
Median Absolute Deviation (MAD)0.1204
Skewness-1.2075847
Sum757.835
Variance0.049917867
MonotonicityNot monotonic
2024-09-24T15:54:32.059430image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7
 
0.7%
0.551 3
 
0.3%
0.8055 3
 
0.3%
0.5767 3
 
0.3%
0.878 3
 
0.3%
0.8448 2
 
0.2%
0.5972 2
 
0.2%
0.6839 2
 
0.2%
0.8586 2
 
0.2%
0.7532 2
 
0.2%
Other values (963) 1034
97.3%
ValueCountFrequency (%)
0.0324 1
0.1%
0.0368 1
0.1%
0.0395 1
0.1%
0.0396 1
0.1%
0.0457 1
0.1%
0.0506 1
0.1%
0.0543 1
0.1%
0.057 1
0.1%
0.0635 1
0.1%
0.0638 1
0.1%
ValueCountFrequency (%)
1 7
0.7%
0.9992 1
 
0.1%
0.9985 1
 
0.1%
0.9955 1
 
0.1%
0.995 1
 
0.1%
0.9948 1
 
0.1%
0.9947 1
 
0.1%
0.9946 2
 
0.2%
0.9945 1
 
0.1%
0.9918 1
 
0.1%

In-State_Tuition
Real number (ℝ)

HIGH CORRELATION 

Distinct1014
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28344.663
Minimum0
Maximum68365
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:32.154224image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7400.5
Q111123.5
median27140
Q341593
95-th percentile61437.6
Maximum68365
Range68365
Interquartile range (IQR)30469.5

Descriptive statistics

Standard deviation17932.823
Coefficient of variation (CV)0.63267018
Kurtosis-1.0650337
Mean28344.663
Median Absolute Deviation (MAD)15557
Skewness0.42698209
Sum30130377
Variance3.2158614 × 108
MonotonicityNot monotonic
2024-09-24T15:54:32.248510image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15140 6
 
0.6%
7941 5
 
0.5%
14340 5
 
0.5%
15904 4
 
0.4%
43670 3
 
0.3%
41600 2
 
0.2%
30680 2
 
0.2%
19800 2
 
0.2%
27000 2
 
0.2%
8008 2
 
0.2%
Other values (1004) 1030
96.9%
ValueCountFrequency (%)
0 2
0.2%
1008 1
0.1%
2960 1
0.1%
3165 1
0.1%
3336 1
0.1%
3356 1
0.1%
3475 1
0.1%
3483 1
0.1%
3906 1
0.1%
4304 1
0.1%
ValueCountFrequency (%)
68365 1
0.1%
66490 1
0.1%
66139 1
0.1%
65844 1
0.1%
65222 1
0.1%
65146 1
0.1%
65028 1
0.1%
64800 1
0.1%
64760 1
0.1%
64726 1
0.1%

Out-of-State_Tuition
Real number (ℝ)

HIGH CORRELATION 

Distinct1015
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32938.382
Minimum0
Maximum68365
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:32.355941image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12575.7
Q120963
median31592
Q341990
95-th percentile61437.6
Maximum68365
Range68365
Interquartile range (IQR)21027

Descriptive statistics

Standard deviation14716.264
Coefficient of variation (CV)0.44678163
Kurtosis-0.61760567
Mean32938.382
Median Absolute Deviation (MAD)10528
Skewness0.42254648
Sum35013500
Variance2.1656843 × 108
MonotonicityNot monotonic
2024-09-24T15:54:32.458292image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24834 6
 
0.6%
23602 5
 
0.5%
21301 5
 
0.5%
26370 4
 
0.4%
27000 3
 
0.3%
43670 3
 
0.3%
25880 3
 
0.3%
41600 2
 
0.2%
32734 2
 
0.2%
30680 2
 
0.2%
Other values (1005) 1028
96.7%
ValueCountFrequency (%)
0 2
0.2%
1008 1
0.1%
4128 1
0.1%
4536 1
0.1%
5354 1
0.1%
5954 1
0.1%
6250 1
0.1%
6304 1
0.1%
7291 1
0.1%
7304 1
0.1%
ValueCountFrequency (%)
68365 1
0.1%
66490 1
0.1%
66139 1
0.1%
65844 1
0.1%
65222 1
0.1%
65146 1
0.1%
65028 1
0.1%
64800 1
0.1%
64760 1
0.1%
64726 1
0.1%

Student_Size
Real number (ℝ)

Distinct982
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5325.6096
Minimum50
Maximum57874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:32.574492image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile475.3
Q11167.5
median2344
Q35971
95-th percentile21564.8
Maximum57874
Range57824
Interquartile range (IQR)4803.5

Descriptive statistics

Standard deviation7602.2776
Coefficient of variation (CV)1.4274943
Kurtosis9.7677507
Mean5325.6096
Median Absolute Deviation (MAD)1501
Skewness2.8793538
Sum5661123
Variance57794624
MonotonicityNot monotonic
2024-09-24T15:54:32.679479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1115 5
 
0.5%
662 3
 
0.3%
2174 3
 
0.3%
1401 3
 
0.3%
245 3
 
0.3%
1362 2
 
0.2%
689 2
 
0.2%
1512 2
 
0.2%
1051 2
 
0.2%
1307 2
 
0.2%
Other values (972) 1036
97.5%
ValueCountFrequency (%)
50 1
0.1%
71 1
0.1%
76 1
0.1%
95 1
0.1%
102 1
0.1%
121 1
0.1%
149 1
0.1%
154 1
0.1%
162 1
0.1%
175 1
0.1%
ValueCountFrequency (%)
57874 1
0.1%
56792 1
0.1%
45140 1
0.1%
42213 1
0.1%
41417 1
0.1%
40980 1
0.1%
39277 1
0.1%
39021 1
0.1%
38438 1
0.1%
37979 1
0.1%

Average_SAT_Score
Real number (ℝ)

HIGH CORRELATION 

Distinct445
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1172.492
Minimum850
Maximum1560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:32.776642image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum850
5-th percentile971
Q11079
median1147
Q31250
95-th percentile1472.9
Maximum1560
Range710
Interquartile range (IQR)171

Descriptive statistics

Standard deviation143.34507
Coefficient of variation (CV)0.12225676
Kurtosis0.10619354
Mean1172.492
Median Absolute Deviation (MAD)85
Skewness0.6563899
Sum1246359
Variance20547.809
MonotonicityNot monotonic
2024-09-24T15:54:32.873455image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1090 33
 
3.1%
1050 28
 
2.6%
1120 17
 
1.6%
1150 15
 
1.4%
1220 12
 
1.1%
1190 11
 
1.0%
1147 9
 
0.8%
1110 9
 
0.8%
1020 9
 
0.8%
1089 8
 
0.8%
Other values (435) 912
85.8%
ValueCountFrequency (%)
850 1
0.1%
862 1
0.1%
870 1
0.1%
871 1
0.1%
878 1
0.1%
887 1
0.1%
889 1
0.1%
890 1
0.1%
895 1
0.1%
896 1
0.1%
ValueCountFrequency (%)
1560 1
 
0.1%
1554 1
 
0.1%
1553 3
0.3%
1547 2
 
0.2%
1546 5
0.5%
1540 2
 
0.2%
1539 2
 
0.2%
1533 1
 
0.1%
1532 1
 
0.1%
1527 2
 
0.2%

Median_Earnings_10_Years_After
Real number (ℝ)

HIGH CORRELATION 

Distinct1002
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58581.38
Minimum0
Maximum143372
Zeros8
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:32.979548image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile39208.2
Q148786
median55933
Q365373
95-th percentile88658.9
Maximum143372
Range143372
Interquartile range (IQR)16587

Descriptive statistics

Standard deviation16234.801
Coefficient of variation (CV)0.27713244
Kurtosis4.1269938
Mean58581.38
Median Absolute Deviation (MAD)7754
Skewness1.0152545
Sum62272007
Variance2.6356876 × 108
MonotonicityNot monotonic
2024-09-24T15:54:33.083084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
63435 19
 
1.8%
0 8
 
0.8%
73997 4
 
0.4%
66125 4
 
0.4%
84131 3
 
0.3%
47384 2
 
0.2%
58561 2
 
0.2%
60249 2
 
0.2%
45454 2
 
0.2%
69020 2
 
0.2%
Other values (992) 1015
95.5%
ValueCountFrequency (%)
0 8
0.8%
21256 1
 
0.1%
21790 1
 
0.1%
27997 1
 
0.1%
30626 1
 
0.1%
30958 1
 
0.1%
31902 1
 
0.1%
31919 1
 
0.1%
32275 1
 
0.1%
32465 1
 
0.1%
ValueCountFrequency (%)
143372 1
0.1%
138687 1
0.1%
137047 1
0.1%
131426 1
0.1%
129455 1
0.1%
125557 1
0.1%
124080 1
0.1%
123938 1
0.1%
120959 1
0.1%
114862 1
0.1%

Completion_Rate
Real number (ℝ)

HIGH CORRELATION 

Distinct981
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60456388
Minimum0.093
Maximum0.9744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:33.186635image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.093
5-th percentile0.30841
Q10.4849
median0.605
Q30.73115
95-th percentile0.89995
Maximum0.9744
Range0.8814
Interquartile range (IQR)0.24625

Descriptive statistics

Standard deviation0.17541679
Coefficient of variation (CV)0.29015426
Kurtosis-0.4475251
Mean0.60456388
Median Absolute Deviation (MAD)0.123
Skewness-0.10421235
Sum642.6514
Variance0.030771049
MonotonicityNot monotonic
2024-09-24T15:54:33.296142image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.684 3
 
0.3%
0.4064 3
 
0.3%
0.658 3
 
0.3%
0.5547 3
 
0.3%
0.5208 3
 
0.3%
0.4588 2
 
0.2%
0.78 2
 
0.2%
0.7307 2
 
0.2%
0.5263 2
 
0.2%
0.87 2
 
0.2%
Other values (971) 1038
97.6%
ValueCountFrequency (%)
0.093 1
0.1%
0.1014 1
0.1%
0.1244 1
0.1%
0.1613 1
0.1%
0.1623 1
0.1%
0.1745 1
0.1%
0.1815 1
0.1%
0.1827 1
0.1%
0.1836 1
0.1%
0.2016 1
0.1%
ValueCountFrequency (%)
0.9744 1
0.1%
0.9736 1
0.1%
0.9726 1
0.1%
0.9625 1
0.1%
0.9615 1
0.1%
0.9612 1
0.1%
0.9587 1
0.1%
0.9574 1
0.1%
0.9557 1
0.1%
0.9548 1
0.1%

Pell_Grant_Rate
Real number (ℝ)

HIGH CORRELATION 

Distinct953
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.30956369
Minimum0
Maximum0.8332
Zeros6
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:33.400443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13051
Q10.21105
median0.2966
Q30.3862
95-th percentile0.5435
Maximum0.8332
Range0.8332
Interquartile range (IQR)0.17515

Descriptive statistics

Standard deviation0.13209031
Coefficient of variation (CV)0.42669834
Kurtosis0.84040594
Mean0.30956369
Median Absolute Deviation (MAD)0.0877
Skewness0.74625693
Sum329.0662
Variance0.017447851
MonotonicityNot monotonic
2024-09-24T15:54:33.545110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
0.6%
0.3985 3
 
0.3%
0.2135 3
 
0.3%
0.3261 3
 
0.3%
0.3921 3
 
0.3%
0.1949 3
 
0.3%
0.369 3
 
0.3%
0.2933 3
 
0.3%
0.215 2
 
0.2%
0.1373 2
 
0.2%
Other values (943) 1032
97.1%
ValueCountFrequency (%)
0 6
0.6%
0.0625 1
 
0.1%
0.0685 1
 
0.1%
0.0736 1
 
0.1%
0.0775 1
 
0.1%
0.0916 1
 
0.1%
0.0921 1
 
0.1%
0.0932 1
 
0.1%
0.0943 1
 
0.1%
0.0952 1
 
0.1%
ValueCountFrequency (%)
0.8332 1
0.1%
0.8161 1
0.1%
0.804 1
0.1%
0.7632 1
0.1%
0.7487 1
0.1%
0.7338 1
0.1%
0.7299 1
0.1%
0.728 1
0.1%
0.7172 1
0.1%
0.6976 1
0.1%
Distinct1056
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size16.6 KiB
2024-09-24T15:54:34.075278image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length25.44873
Min length11

Characters and Unicode

Total characters27052
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1051 ?
Unique (%)98.9%

Sample

1st rowAlabama A & M University
2nd rowUniversity of Alabama at Birmingham
3rd rowUniversity of Alabama in Huntsville
4th rowAlabama State University
5th rowThe University of Alabama
ValueCountFrequency (%)
university 677
 
19.9%
college 282
 
8.3%
of 267
 
7.9%
state 158
 
4.7%
the 39
 
1.1%
at 37
 
1.1%
saint 28
 
0.8%
pennsylvania 28
 
0.8%
campus 26
 
0.8%
texas 25
 
0.7%
Other values (979) 1828
53.8%
2024-09-24T15:54:34.507402image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2683
 
9.9%
i 2515
 
9.3%
2334
 
8.6%
n 1978
 
7.3%
t 1953
 
7.2%
r 1582
 
5.8%
s 1503
 
5.6%
a 1481
 
5.5%
o 1477
 
5.5%
l 1257
 
4.6%
Other values (49) 8289
30.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27052
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2683
 
9.9%
i 2515
 
9.3%
2334
 
8.6%
n 1978
 
7.3%
t 1953
 
7.2%
r 1582
 
5.8%
s 1503
 
5.6%
a 1481
 
5.5%
o 1477
 
5.5%
l 1257
 
4.6%
Other values (49) 8289
30.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27052
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2683
 
9.9%
i 2515
 
9.3%
2334
 
8.6%
n 1978
 
7.3%
t 1953
 
7.2%
r 1582
 
5.8%
s 1503
 
5.6%
a 1481
 
5.5%
o 1477
 
5.5%
l 1257
 
4.6%
Other values (49) 8289
30.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27052
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2683
 
9.9%
i 2515
 
9.3%
2334
 
8.6%
n 1978
 
7.3%
t 1953
 
7.2%
r 1582
 
5.8%
s 1503
 
5.6%
a 1481
 
5.5%
o 1477
 
5.5%
l 1257
 
4.6%
Other values (49) 8289
30.6%

Interactions

2024-09-24T15:54:31.031107image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.477767image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.150445image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.730050image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.306025image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.989329image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.902918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.680486image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.127192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.587621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.221315image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.799376image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.378729image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.091913image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.981658image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.766188image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.222332image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.709635image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.297145image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.871022image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.456536image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.204106image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.069171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.856625image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.307076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.804838image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.369979image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.944986image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.542156image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.322803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.171791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.940560image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.382976image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.887199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.439481image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.015634image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.623169image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.430642image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.274201image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:30.027654image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.458888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:25.955532image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.511551image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.089813image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.710731image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.596586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.391474image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:30.489074image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.540911image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.026394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.592385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.165511image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.798747image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.732058image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.494595image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:30.576001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:31.610300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.089598image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:26.662987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.235355image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:27.888832image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:28.822433image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:29.586007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-24T15:54:30.910096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-09-24T15:54:34.697807image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Admission_RateAverage_SAT_ScoreCompletion_RateIn-State_TuitionMedian_Earnings_10_Years_AfterOut-of-State_TuitionPell_Grant_RateStudent_Size
Admission_Rate1.000-0.380-0.389-0.340-0.243-0.3330.2670.020
Average_SAT_Score-0.3801.0000.8290.5610.6830.689-0.7170.275
Completion_Rate-0.3890.8291.0000.5840.6710.692-0.7170.268
In-State_Tuition-0.3400.5610.5841.0000.5040.900-0.444-0.254
Median_Earnings_10_Years_After-0.2430.6830.6710.5041.0000.626-0.5720.294
Out-of-State_Tuition-0.3330.6890.6920.9000.6261.000-0.530-0.017
Pell_Grant_Rate0.267-0.717-0.717-0.444-0.572-0.5301.000-0.227
Student_Size0.0200.2750.268-0.2540.294-0.017-0.2271.000

Missing values

2024-09-24T15:54:31.710549image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-24T15:54:31.826684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Admission_RateIn-State_TuitionOut-of-State_TuitionStudent_SizeAverage_SAT_ScoreMedian_Earnings_10_Years_AfterCompletion_RatePell_Grant_RateCollege_Name
00.684010024186345196920.0406280.27380.6536Alabama A & M University
10.8668883221216127761291.0545010.63530.3308University of Alabama at Birmingham
30.7810118782477069851259.0617670.61920.2173University of Alabama in Huntsville
40.966011068193963296963.0345020.28060.6976Alabama State University
50.80061194032300313601304.0592210.72500.1788The University of Alabama
80.922391001934833071051.0443910.35770.4589Auburn University at Montgomery
90.43741217632960252341292.0653370.80820.1254Auburn University
100.571721250212509681218.0594810.67620.2268Birmingham-Southern College
150.8241239202392015871021.0434570.25950.4610Faulkner University
220.659528350283508101086.0496010.47350.3921Huntingdon College
Admission_RateIn-State_TuitionOut-of-State_TuitionStudent_SizeAverage_SAT_ScoreMedian_Earnings_10_Years_AfterCompletion_RatePell_Grant_RateCollege_Name
44080.6637361003610010581301.0798780.58550.2327DigiPen Institute of Technology
44810.875526505265055171120.0978270.56840.6654Neumont College of Computer Science
44820.7334384423844211401023.0434180.53260.5428Johnson & Wales University-Charlotte
46110.204120000200002081120.0359330.20510.4444Visible Music College
46960.758528425284253761356.000.68330.0000Patrick Henry College
47120.452721690216902901302.0580650.56960.2266The King's College
47570.66030033791000.0660870.30810.5660Jersey College
48220.717013464134646171190.0690200.54080.3700University of Minnesota-Rochester
49361.0000184501845050954.0340860.74070.3514Compass College of Film and Media
49510.96099548227646404954.0543380.31400.4914Texas A&M University-San Antonio